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    <title>topic Urgency: How to do Data Migration task using Databricks Lakebridge tool ? in Data Engineering</title>
    <link>https://community.databricks.com/t5/data-engineering/urgency-how-to-do-data-migration-task-using-databricks/m-p/138326#M50914</link>
    <description>&lt;P&gt;Dear community expert,&lt;/P&gt;&lt;P&gt;I have completed two phases &lt;STRONG&gt;Analyzer&lt;/STRONG&gt; &amp;amp; &lt;STRONG&gt;Converter&lt;/STRONG&gt; of &lt;STRONG&gt;Databricks Lakebridge&lt;/STRONG&gt; but stuck at migrating data from source to target using lakebridge. I have watched &lt;STRONG&gt;BrickBites Series on Lakebridge&lt;/STRONG&gt; but did not find on how to migrate data from source to target. I need guidance on how I should migrate data like tables, views from source to target so that I can proceed for reconciliation phase to validate schema and data. As, I have taken &lt;U&gt;&lt;STRONG&gt;Snowflake as a source with few sample tables and queries to migrate on Databricks Platform as a target&lt;/STRONG&gt;&lt;/U&gt;.&lt;/P&gt;&lt;P&gt;Thank you !!&lt;/P&gt;</description>
    <pubDate>Mon, 10 Nov 2025 04:28:15 GMT</pubDate>
    <dc:creator>shubham007</dc:creator>
    <dc:date>2025-11-10T04:28:15Z</dc:date>
    <item>
      <title>Urgency: How to do Data Migration task using Databricks Lakebridge tool ?</title>
      <link>https://community.databricks.com/t5/data-engineering/urgency-how-to-do-data-migration-task-using-databricks/m-p/138326#M50914</link>
      <description>&lt;P&gt;Dear community expert,&lt;/P&gt;&lt;P&gt;I have completed two phases &lt;STRONG&gt;Analyzer&lt;/STRONG&gt; &amp;amp; &lt;STRONG&gt;Converter&lt;/STRONG&gt; of &lt;STRONG&gt;Databricks Lakebridge&lt;/STRONG&gt; but stuck at migrating data from source to target using lakebridge. I have watched &lt;STRONG&gt;BrickBites Series on Lakebridge&lt;/STRONG&gt; but did not find on how to migrate data from source to target. I need guidance on how I should migrate data like tables, views from source to target so that I can proceed for reconciliation phase to validate schema and data. As, I have taken &lt;U&gt;&lt;STRONG&gt;Snowflake as a source with few sample tables and queries to migrate on Databricks Platform as a target&lt;/STRONG&gt;&lt;/U&gt;.&lt;/P&gt;&lt;P&gt;Thank you !!&lt;/P&gt;</description>
      <pubDate>Mon, 10 Nov 2025 04:28:15 GMT</pubDate>
      <guid>https://community.databricks.com/t5/data-engineering/urgency-how-to-do-data-migration-task-using-databricks/m-p/138326#M50914</guid>
      <dc:creator>shubham007</dc:creator>
      <dc:date>2025-11-10T04:28:15Z</dc:date>
    </item>
    <item>
      <title>Re: Urgency: How to do Data Migration task using Databricks Lakebridge tool ?</title>
      <link>https://community.databricks.com/t5/data-engineering/urgency-how-to-do-data-migration-task-using-databricks/m-p/138628#M50982</link>
      <description>&lt;P&gt;&lt;STRONG&gt;Lakebridge doesn’t copy data.&lt;/STRONG&gt; It covers &lt;STRONG&gt;Assessment → Conversion (Analyzer/Converter) → Reconciliation&lt;/STRONG&gt;.&lt;/P&gt;&lt;P&gt;The fastest way is to use &lt;STRONG&gt;Lakehouse Federation.&lt;/STRONG&gt;&amp;nbsp;Create a &lt;STRONG&gt;Snowflake connection&lt;/STRONG&gt; in Unity Catalog and run federated queries from Databricks. For permanent migration, materialize with CREATE TABLE AS SELECT into Delta.&lt;/P&gt;</description>
      <pubDate>Tue, 11 Nov 2025 17:02:37 GMT</pubDate>
      <guid>https://community.databricks.com/t5/data-engineering/urgency-how-to-do-data-migration-task-using-databricks/m-p/138628#M50982</guid>
      <dc:creator>bianca_unifeye</dc:creator>
      <dc:date>2025-11-11T17:02:37Z</dc:date>
    </item>
    <item>
      <title>Re: Urgency: How to do Data Migration task using Databricks Lakebridge tool ?</title>
      <link>https://community.databricks.com/t5/data-engineering/urgency-how-to-do-data-migration-task-using-databricks/m-p/138810#M51017</link>
      <description>&lt;P class="my-2 [&amp;amp;+p]:mt-4 [&amp;amp;_strong:has(+br)]:inline-block [&amp;amp;_strong:has(+br)]:pb-2"&gt;To migrate tables and views from Snowflake (source) to Databricks (target) using Lakebridge, you must export your data from Snowflake into a supported cloud storage (usually as Parquet files), then import these files into Databricks Delta tables. Lakebridge simplifies the overall process—especially for code, schema conversion, and reconciliation—but the physical migration of large volumes of data is performed via staging to cloud storage and loading into Databricks.​​&lt;/P&gt;
&lt;H2 id="step-by-step-data-migration-process" class="mb-2 mt-4 font-display font-semimedium text-base first:mt-0 md:text-lg [hr+&amp;amp;]:mt-4"&gt;Step-by-Step Data Migration Process&lt;/H2&gt;
&lt;H2 class="mb-2 mt-4 font-display font-semimedium text-base first:mt-0"&gt;1. Export Data from Snowflake&lt;/H2&gt;
&lt;UL class="marker:text-quiet list-disc"&gt;
&lt;LI class="py-0 my-0 prose-p:pt-0 prose-p:mb-2 prose-p:my-0 [&amp;amp;&amp;gt;p]:pt-0 [&amp;amp;&amp;gt;p]:mb-2 [&amp;amp;&amp;gt;p]:my-0"&gt;
&lt;P class="my-2 [&amp;amp;+p]:mt-4 [&amp;amp;_strong:has(+br)]:inline-block [&amp;amp;_strong:has(+br)]:pb-2"&gt;Use the Snowflake COPY INTO command to export your tables as Parquet files to a cloud storage bucket (S3, ADLS, or GCS). Example:&lt;/P&gt;
&lt;DIV class="w-full md:max-w-[90vw]"&gt;
&lt;DIV class="codeWrapper text-light selection:text-super selection:bg-super/10 my-md relative flex flex-col rounded font-mono text-sm font-normal bg-subtler"&gt;
&lt;DIV class="translate-y-xs -translate-x-xs bottom-xl mb-xl flex h-0 items-start justify-end md:sticky md:top-[100px]"&gt;
&lt;DIV class="overflow-hidden rounded-full border-subtlest ring-subtlest divide-subtlest bg-base"&gt;
&lt;DIV class="border-subtlest ring-subtlest divide-subtlest bg-subtler"&gt;&amp;nbsp;&lt;/DIV&gt;
&lt;/DIV&gt;
&lt;/DIV&gt;
&lt;DIV class="-mt-xl"&gt;
&lt;DIV&gt;
&lt;DIV class="text-quiet bg-subtle py-xs px-sm inline-block rounded-br rounded-tl-[3px] font-thin" data-testid="code-language-indicator"&gt;text&lt;/DIV&gt;
&lt;/DIV&gt;
&lt;DIV&gt;&lt;SPAN&gt;&lt;CODE&gt;COPY INTO 's3://your-bucket/path/'
FROM my_database.my_schema.my_table
FILE_FORMAT = (TYPE = PARQUET COMPRESSION = SNAPPY);
&lt;/CODE&gt;&lt;/SPAN&gt;&lt;/DIV&gt;
&lt;/DIV&gt;
&lt;/DIV&gt;
&lt;/DIV&gt;
&lt;/LI&gt;
&lt;LI class="py-0 my-0 prose-p:pt-0 prose-p:mb-2 prose-p:my-0 [&amp;amp;&amp;gt;p]:pt-0 [&amp;amp;&amp;gt;p]:mb-2 [&amp;amp;&amp;gt;p]:my-0"&gt;
&lt;P class="my-2 [&amp;amp;+p]:mt-4 [&amp;amp;_strong:has(+br)]:inline-block [&amp;amp;_strong:has(+br)]:pb-2"&gt;For large tables, use partitioning for export efficiency (e.g., partition by date column).​&lt;/P&gt;
&lt;/LI&gt;
&lt;/UL&gt;
&lt;H2 class="mb-2 mt-4 font-display font-semimedium text-base first:mt-0"&gt;2. Set Up Cloud Storage Access in Databricks&lt;/H2&gt;
&lt;UL class="marker:text-quiet list-disc"&gt;
&lt;LI class="py-0 my-0 prose-p:pt-0 prose-p:mb-2 prose-p:my-0 [&amp;amp;&amp;gt;p]:pt-0 [&amp;amp;&amp;gt;p]:mb-2 [&amp;amp;&amp;gt;p]:my-0"&gt;
&lt;P class="my-2 [&amp;amp;+p]:mt-4 [&amp;amp;_strong:has(+br)]:inline-block [&amp;amp;_strong:has(+br)]:pb-2"&gt;Ensure Databricks has access to your storage location by configuring the necessary credentials and permissions.&lt;/P&gt;
&lt;/LI&gt;
&lt;/UL&gt;
&lt;H2 class="mb-2 mt-4 font-display font-semimedium text-base first:mt-0"&gt;3. Load Data into Databricks Delta Tables&lt;/H2&gt;
&lt;UL class="marker:text-quiet list-disc"&gt;
&lt;LI class="py-0 my-0 prose-p:pt-0 prose-p:mb-2 prose-p:my-0 [&amp;amp;&amp;gt;p]:pt-0 [&amp;amp;&amp;gt;p]:mb-2 [&amp;amp;&amp;gt;p]:my-0"&gt;
&lt;P class="my-2 [&amp;amp;+p]:mt-4 [&amp;amp;_strong:has(+br)]:inline-block [&amp;amp;_strong:has(+br)]:pb-2"&gt;Use Databricks Notebooks or workflows to create Delta tables and load data from Parquet files:&lt;/P&gt;
&lt;DIV class="w-full md:max-w-[90vw]"&gt;
&lt;DIV class="codeWrapper text-light selection:text-super selection:bg-super/10 my-md relative flex flex-col rounded font-mono text-sm font-normal bg-subtler"&gt;
&lt;DIV class="translate-y-xs -translate-x-xs bottom-xl mb-xl flex h-0 items-start justify-end md:sticky md:top-[100px]"&gt;
&lt;DIV class="overflow-hidden rounded-full border-subtlest ring-subtlest divide-subtlest bg-base"&gt;
&lt;DIV class="border-subtlest ring-subtlest divide-subtlest bg-subtler"&gt;&amp;nbsp;&lt;/DIV&gt;
&lt;/DIV&gt;
&lt;/DIV&gt;
&lt;DIV class="-mt-xl"&gt;
&lt;DIV&gt;
&lt;DIV class="text-quiet bg-subtle py-xs px-sm inline-block rounded-br rounded-tl-[3px] font-thin" data-testid="code-language-indicator"&gt;python&lt;/DIV&gt;
&lt;/DIV&gt;
&lt;DIV&gt;&lt;SPAN&gt;&lt;CODE&gt;df &lt;SPAN class="token token operator"&gt;=&lt;/SPAN&gt; spark&lt;SPAN class="token token punctuation"&gt;.&lt;/SPAN&gt;read&lt;SPAN class="token token punctuation"&gt;.&lt;/SPAN&gt;&lt;SPAN class="token token"&gt;format&lt;/SPAN&gt;&lt;SPAN class="token token punctuation"&gt;(&lt;/SPAN&gt;&lt;SPAN class="token token"&gt;"parquet"&lt;/SPAN&gt;&lt;SPAN class="token token punctuation"&gt;)&lt;/SPAN&gt;&lt;SPAN class="token token punctuation"&gt;.&lt;/SPAN&gt;load&lt;SPAN class="token token punctuation"&gt;(&lt;/SPAN&gt;&lt;SPAN class="token token"&gt;"s3://your-bucket/path/"&lt;/SPAN&gt;&lt;SPAN class="token token punctuation"&gt;)&lt;/SPAN&gt;
df&lt;SPAN class="token token punctuation"&gt;.&lt;/SPAN&gt;write&lt;SPAN class="token token punctuation"&gt;.&lt;/SPAN&gt;&lt;SPAN class="token token"&gt;format&lt;/SPAN&gt;&lt;SPAN class="token token punctuation"&gt;(&lt;/SPAN&gt;&lt;SPAN class="token token"&gt;"delta"&lt;/SPAN&gt;&lt;SPAN class="token token punctuation"&gt;)&lt;/SPAN&gt;&lt;SPAN class="token token punctuation"&gt;.&lt;/SPAN&gt;save&lt;SPAN class="token token punctuation"&gt;(&lt;/SPAN&gt;&lt;SPAN class="token token"&gt;"/mnt/delta/target_table"&lt;/SPAN&gt;&lt;SPAN class="token token punctuation"&gt;)&lt;/SPAN&gt;
&lt;/CODE&gt;&lt;/SPAN&gt;&lt;/DIV&gt;
&lt;/DIV&gt;
&lt;/DIV&gt;
&lt;/DIV&gt;
&lt;/LI&gt;
&lt;LI class="py-0 my-0 prose-p:pt-0 prose-p:mb-2 prose-p:my-0 [&amp;amp;&amp;gt;p]:pt-0 [&amp;amp;&amp;gt;p]:mb-2 [&amp;amp;&amp;gt;p]:my-0"&gt;
&lt;P class="my-2 [&amp;amp;+p]:mt-4 [&amp;amp;_strong:has(+br)]:inline-block [&amp;amp;_strong:has(+br)]:pb-2"&gt;For continuous/streaming loads, use Auto Loader or Databricks workflows for incremental or live updates.​&lt;/P&gt;
&lt;/LI&gt;
&lt;/UL&gt;
&lt;H2 class="mb-2 mt-4 font-display font-semimedium text-base first:mt-0"&gt;4. Migrate and Create Views/SQL Logic&lt;/H2&gt;
&lt;UL class="marker:text-quiet list-disc"&gt;
&lt;LI class="py-0 my-0 prose-p:pt-0 prose-p:mb-2 prose-p:my-0 [&amp;amp;&amp;gt;p]:pt-0 [&amp;amp;&amp;gt;p]:mb-2 [&amp;amp;&amp;gt;p]:my-0"&gt;
&lt;P class="my-2 [&amp;amp;+p]:mt-4 [&amp;amp;_strong:has(+br)]:inline-block [&amp;amp;_strong:has(+br)]:pb-2"&gt;After data migration, convert your Snowflake views and SQL queries using Lakebridge’s Converter. Validate and translate SQL, and deploy scripts in Databricks as new views.&lt;/P&gt;
&lt;/LI&gt;
&lt;/UL&gt;
&lt;H2 class="mb-2 mt-4 font-display font-semimedium text-base first:mt-0"&gt;5. Reconciliation Preparation&lt;/H2&gt;
&lt;UL class="marker:text-quiet list-disc"&gt;
&lt;LI class="py-0 my-0 prose-p:pt-0 prose-p:mb-2 prose-p:my-0 [&amp;amp;&amp;gt;p]:pt-0 [&amp;amp;&amp;gt;p]:mb-2 [&amp;amp;&amp;gt;p]:my-0"&gt;
&lt;P class="my-2 [&amp;amp;+p]:mt-4 [&amp;amp;_strong:has(+br)]:inline-block [&amp;amp;_strong:has(+br)]:pb-2"&gt;Once data and views are migrated, use Lakebridge’s reconciliation tools to compare row counts, aggregates, and schemas between Snowflake and Databricks to ensure fidelity.​&lt;/P&gt;
&lt;/LI&gt;
&lt;/UL&gt;
&lt;H2 id="key-reminders" class="mb-2 mt-4 font-display font-semimedium text-base first:mt-0 md:text-lg [hr+&amp;amp;]:mt-4"&gt;Key Reminders&lt;/H2&gt;
&lt;UL class="marker:text-quiet list-disc"&gt;
&lt;LI class="py-0 my-0 prose-p:pt-0 prose-p:mb-2 prose-p:my-0 [&amp;amp;&amp;gt;p]:pt-0 [&amp;amp;&amp;gt;p]:mb-2 [&amp;amp;&amp;gt;p]:my-0"&gt;
&lt;P class="my-2 [&amp;amp;+p]:mt-4 [&amp;amp;_strong:has(+br)]:inline-block [&amp;amp;_strong:has(+br)]:pb-2"&gt;For metadata (schema, DDLs), leverage Lakebridge Analyzer and Converter.&lt;/P&gt;
&lt;/LI&gt;
&lt;LI class="py-0 my-0 prose-p:pt-0 prose-p:mb-2 prose-p:my-0 [&amp;amp;&amp;gt;p]:pt-0 [&amp;amp;&amp;gt;p]:mb-2 [&amp;amp;&amp;gt;p]:my-0"&gt;
&lt;P class="my-2 [&amp;amp;+p]:mt-4 [&amp;amp;_strong:has(+br)]:inline-block [&amp;amp;_strong:has(+br)]:pb-2"&gt;For data movement, use Parquet via cloud storage as the most compatible path.&lt;/P&gt;
&lt;/LI&gt;
&lt;LI class="py-0 my-0 prose-p:pt-0 prose-p:mb-2 prose-p:my-0 [&amp;amp;&amp;gt;p]:pt-0 [&amp;amp;&amp;gt;p]:mb-2 [&amp;amp;&amp;gt;p]:my-0"&gt;
&lt;P class="my-2 [&amp;amp;+p]:mt-4 [&amp;amp;_strong:has(+br)]:inline-block [&amp;amp;_strong:has(+br)]:pb-2"&gt;Automation: For many tables, script the process or employ Databricks batch jobs for efficiency.​&lt;/P&gt;
&lt;/LI&gt;
&lt;LI class="py-0 my-0 prose-p:pt-0 prose-p:mb-2 prose-p:my-0 [&amp;amp;&amp;gt;p]:pt-0 [&amp;amp;&amp;gt;p]:mb-2 [&amp;amp;&amp;gt;p]:my-0"&gt;
&lt;P class="my-2 [&amp;amp;+p]:mt-4 [&amp;amp;_strong:has(+br)]:inline-block [&amp;amp;_strong:has(+br)]:pb-2"&gt;After migration, update your BI or analytics tools to point to Databricks tables/views.&lt;/P&gt;
&lt;/LI&gt;
&lt;/UL&gt;
&lt;P class="my-2 [&amp;amp;+p]:mt-4 [&amp;amp;_strong:has(+br)]:inline-block [&amp;amp;_strong:has(+br)]:pb-2"&gt;This approach enables a robust, auditable pipeline that supports reconciliation and validation for accurate migration outcomes, which is vital before advancing to the reconciliation phase.&lt;/P&gt;</description>
      <pubDate>Wed, 12 Nov 2025 16:48:11 GMT</pubDate>
      <guid>https://community.databricks.com/t5/data-engineering/urgency-how-to-do-data-migration-task-using-databricks/m-p/138810#M51017</guid>
      <dc:creator>mark_ott</dc:creator>
      <dc:date>2025-11-12T16:48:11Z</dc:date>
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